Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate init...
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Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping *** learning methods have been applied in musculoskeletal imaging,but need a large amount of data for *** by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and *** the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue *** results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best *** specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.
In recent years, we have witnessed the generation of exceptional authentic deepfake images and videos due to the availability of cutting-edge Artificial Intelligence and deep learning techniques. Deepfakes represent s...
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This research examines how Nextgen wireless systems can benefit from Orthogonal Time Frequency Space (OTFS) modulation in different high-mobility channel situations. We test the BER performance of OTFS and OFDM with v...
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Emotions are intrinsic to human nature, playing a vital role in human cognition. Emotions are closely intertwined with rational decision-making, perception, human interaction, and human intelligence. EEG has emerged a...
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Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive *** detection methods often fail to keep pace with the evolving ...
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Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive *** detection methods often fail to keep pace with the evolving sophistication of cyber *** paper introduces a novel hybrid ensemble learning framework that leverages a combination of advanced machine learning algorithms—Logistic Regression(LR),Support Vector Machines(SVM),eXtreme Gradient Boosting(XGBoost),Categorical Boosting(CatBoost),and Deep Neural Networks(DNN).Utilizing the XSS-Attacks-2021 dataset,which comprises 460 instances across various real-world trafficrelated scenarios,this framework significantly enhances XSS attack *** approach,which includes rigorous feature engineering and model tuning,not only optimizes accuracy but also effectively minimizes false positives(FP)(0.13%)and false negatives(FN)(0.19%).This comprehensive methodology has been rigorously validated,achieving an unprecedented accuracy of 99.87%.The proposed system is scalable and efficient,capable of adapting to the increasing number of web applications and user demands without a decline in *** demonstrates exceptional real-time capabilities,with the ability to detect XSS attacks dynamically,maintaining high accuracy and low latency even under significant ***,despite the computational complexity introduced by the hybrid ensemble approach,strategic use of parallel processing and algorithm tuning ensures that the system remains scalable and performs robustly in real-time *** for easy integration with existing web security systems,our framework supports adaptable Application Programming Interfaces(APIs)and a modular design,facilitating seamless augmentation of current *** innovation represents a significant advancement in cybersecurity,offering a scalable and effective solution for securing modern web applications against evolving threats.
Due to the advancements in cutting-edge generative AI algorithms, generating hyper realistic deepfake videos has become easier for the public. This hyperrealism consequently fails contemporary methods to reliably disc...
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Due to the advancements in cutting-edge generative AI algorithms, generating hyper realistic deepfake videos has become easier for the public. This hyperrealism consequently fails contemporary methods to reliably discriminate between original and fake videos. Therefore, to counter any threat caused by these next-generation artificially generated videos, dependable approaches are required to address this classification challenge. To achieve this objective this paper presents an interdisciplinary approach that integrates game theory with deep learning to bring a novel solution to the problem of deepfake detection and protect the detectors against anti-forensics attack. To the best of our knowledge, there does not exist any other work dedicated to video deepfake detection using the integrated approach of game theory and deep learning. The game is designed for two players to distinguish between pristine and deepfake videos. The game utilizes different strategies for the data manipulator as a player P1 and the deepfake detector as P2. Strategies used for P1 involve the formation of the subsets like open and close-set, combined subsets, imbalanced dataset, and post-processing attacks to create challenging strategies for P2. To counter the strategies of P1,we propose a novel Regularized Forensic Efficient Net (RFE Net) that employs regularization techniques, such as batch normalization, dropout, augmentation, and early stopping. Based on the P1 move, the detector chooses the regularization techniques by considering factors such as generalizability and efficiency. Regularization-based strategies improve the performance of our model when compared to contemporary methods. Computation of the Nash equilibrium with the proposed zero-sum game helps to effectively detect deepfakes and leads the game to maximum payoff. Performance of the proposed game theory-based RFE Net was measured on standard and diverse datasets of FaceForensic++, DFDC preview, CelebDF, DFFD, and the World lea
Early diagnosis-treatment of melanoma is very important because of its dangerous nature and rapid spread. When diagnosed correctly and early, the recovery rate of patients increases significantly. Physical methods are...
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Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical *** gas analysis(DGA)is frequently used for this ***,DGA lacks the necessary level of accura...
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Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical *** gas analysis(DGA)is frequently used for this ***,DGA lacks the necessary level of accuracy to identify all equipment faults,particularly in their initial stages of ***,it does not have the capability for real-time monitoring and relies on manual sampling and laboratory testing,causing potential delays in fault ***,the interpretation of DGA data necessitates specialised expertise,which may pose difficulties for smaller entities that have limited access to ***,the contribution of this research is to use infrared spectroscopy measurements as a new effective technique substituting the DGA method for fault diagnosis in insulating *** inception faults that were considered in this study were the electrical fault(discharges of high energy)and the thermal fault(300°C
The current urban intelligent transportation is in a rapid development stage, and coherence control of vehicle formations has important implications in urban intelligent transportation research. This article focuses o...
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In the face of an escalating global water crisis,countries worldwide grapple with the crippling effects of scarcity,jeopardizing economic progress and hindering societal *** energy emerges as a beacon of hope,offering...
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In the face of an escalating global water crisis,countries worldwide grapple with the crippling effects of scarcity,jeopardizing economic progress and hindering societal *** energy emerges as a beacon of hope,offering a sustainable and environmentally friendly solution to *** distillation technology,harnessing the power of the sun,transforms seawater into freshwater,expanding the availability of this precious *** solar still performance under specific climatic conditions and evaluating different configurations is crucial for practical implementation and widespread adoption of solar *** this study,we conducted theoretical investigations on three distinct solar still configurations to evaluate their performance under Baghdad’s climatic *** solar stills analyzed include the passive solar still,themodified solar still coupled with a magnetic field,and themodified solar still coupled with bothmagnetic and electrical *** results proved that the evaporation heat transfer coefficient peaked at 14:00,reaching 25.05 W/m^(2).℃for the convention pyramid solar still(CPSS),32.33 W/m^(2).℃for the magnetic pyramid solar still(MPSS),and 40.98 W/m^(2).℃for elecro-magnetic pyramid solar still(EMPSS),highlighting their efficiency in converting solar energy to ***,exergy efficiency remained notably lower,at 1.6%,5.31%,and 7.93%for the three still types,even as energy efficiency reached its maximum of 18.6%at 14:00 with a corresponding peak evaporative heat of 162.4 W/m^(2).
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